Object-oriented querying of existing relational databases

In this paper, we present algorithms which allow an object-oriented querying of existing relational databases. Our goal is to provide an improved query interface for relational systems with better query facilities than SQL. This seems to be very important since, in real world applications, relational systems are most commonly used and their dominance will remain in the near future. To overcome the drawbacks of relational systems, especially the poor query facilities of SQL, we propose a schema transformation and a query translation algorithm. The schema transformation algorithm uses additional semantic information to enhance the relational schema and transform it into a corresponding object-oriented schema. If the additional semantic information can be deducted from an underlying entity-relationship design schema, the schema transformation may be done fully automatically. To query the created object-oriented schema, we use the Structured Object Query Language (SOQL) which provides declarative query facilities on objects. SOQL queries using the created object-oriented schema are much shorter, easier to write and understand and more intuitive than corresponding S Q L queries leading to an enhanced usability and an improved querying of the database. The query translation algorithm automatically translates SOQL queries into equivalent SQL queries for the original relational schema

Implementing imperfect information in fuzzy databases

Information in real-world applications is often vague, imprecise and uncertain. Ignoring the inherent imperfect nature of real-world will undoubtedly introduce some deformation of human perception of real-world and may eliminate several substantial information, which may be very useful in several data-intensive applications. In database context, several fuzzy database models have been proposed. In these works, fuzziness is introduced at different levels. Common to all these proposals is the support of fuzziness at the attribute level. This paper proposes first a rich set of data types devoted to model the different kinds of imperfect information. The paper then proposes a formal approach to implement these data types. The proposed approach was implemented within a relational object database model but it is generic enough to be incorporated into other database models.ou

Las bases de datos descriptivas: Un diseño de Modelo conceptual orientado a objetos

The present theoretical article is the result of an investigation that combines the Systems Engineering and the Library Sciences; it shows an interdisciplinary approach to the problem presented by the descriptive databases of the digital library, problematic generated by the change in the principles of organization of the information and the demands that the digital environment imposes to the libraries. The analysis leads to a rethinking about the construction of descriptive databases, migrating from the Entity–relationship Model (ER model) to adopt the Object-oriented Modeling (OOM), which is currently used for the construction and programmatic development of the semantic web. Therefore, this theoretical article proposes an Object-oriented Conceptual Modeling under its own methodology, which it develops the process to generate the proposed model in two stages. The first is to approach the problem, while the second corresponds to the identification of elements that includes elements of the Resources, Description and Access (RDA) rules and observes the theoretical principles that establish the Functional Fequirements for Bibliographic Records (FRBR). Already as a whole, all data are analyzed to generate the design proposal of three object-oriented conceptual modeling for descriptive databases: 1) the Work model, 2) the Domain model, and 3) the Instance model, to form a more adequate and descriptive database of the library in this digital era

An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database

Integrating Distributed Sources of Information for Construction Cost Estimating using Semantic Web and Semantic Web Service technologies

A construction project requires collaboration of several organizations such as owner, designer, contractor, and material supplier organizations. These organizations need to exchange information to enhance their teamwork. Understanding the information received from other organizations requires specialized human resources. Construction cost estimating is one of the processes that requires information from several sources including a building information model (BIM) created by designers, estimating assembly and work item information maintained by contractors, and construction material cost data provided by material suppliers. Currently, it is not easy to integrate the information necessary for cost estimating over the Internet. This paper discusses a new approach to construction cost estimating that uses Semantic Web technology. Semantic Web technology provides an infrastructure and a data modeling format that enables accessing, combining, and sharing information over the Internet in a machine processable format. The estimating approach presented in this paper relies on BIM, estimating knowledge, and construction material cost data expressed in a web ontology language. The approach presented in this paper makes the various sources of estimating data accessible as Simple Protocol and Resource Description Framework Query Language (SPARQL) endpoints or Semantic Web Services. We present an estimating application that integrates distributed information provided by project designers, contractors, and material suppliers for preparing cost estimates. The purpose of this paper is not to fully automate the estimating process but to streamline it by reducing human involvement in repetitive cost estimating activities